Modal parameters are widely used in bridge damage detection, finite element model (FEM) updating and design optimization. However, the conventional modal identification approaches require large number of sensors, enormous data processing workload, but normally result in mode shapes with low accuracy. This paper proposes a modal identification method of time-varying vehicle-bridge system using a single sensor. Firstly, the essential physical relationship between the instantaneous frequency of the vehicle-bridge system and the bridge mode shapes are derived. Subsequently, based on the synchroextracting transform, the instantaneous frequency of the system is tracked through the dynamic response collected by a single sensor, and further the modal parameters are estimated by using the derived physical relationship. Then numerical and experimental examples are conducted to examine the feasibility and effectiveness of the proposed method. Finally, the modal parameters identified by the proposed method are applied in bridge FEM updating. The results manifest that the proposed method identifies the modal parameters with high accuracy via a single sensor, and can provide reliable data for the FEM updating.

Bridge flexibility matrix is widely used in damage detection and condition assessment. As the mass-normalized mode shapes with high spatial resolution are required in formulating the flexibility matrix, the difficult tasks of measuring excitation and arranging a large number of sensors are normally involved. This paper proposes a flexibility matrix identification method by using the moving vehicle induced responses for beam type bridges. Firstly, the proportional relationship between the modal flexibility matrix and the matrix formulated by the bridge influence lines (ILs) of several points is derived theoretically. Then the quasi-static component response of the moving vehicle induced responses is extracted through the analytical mode decomposition (AMD), and the IL of the measurement point is obtained via polynomial fitting accordingly. Finally the flexibility matrix is formulated based on the measured ILs and the derived proportional relationship, and employed to estimate the static displacement of the bridge. Numerical and experimental examples are conducted to verify the accuracy and feasibility of the proposed method. The results indicate that it can identify the bridge flexibility matrix and estimate the static displacement with high accuracy and efficiency at the cost of few sensors. Besides, the proposed method is insensitive to vehicle parameters (velocity, spring stiffness, wheelbase, and weight), road surface roughness and measurement noise.